Enhanced Oil Recovery Technologies, 4th Edition

A study was conducted on the construction of sulfonated poly(aryl ether ketone) nanomicelles and their dispersion–displacement synergistic behavior in deep oil recovery. Unlike conventional surfactant systems, inorganic nanoparticle-based EOR materials, and polymeric nanofluids that mainly rely on interfacial tension reduction, wettability alteration, or viscosity regulation, this study constructs self-assembled sulfonated poly(aryl ether ketone) nanomicelles that integrate a rigid aromatic backbone, ionizable sulfonic acid groups, nanoscale dispersion, and interfacial regulation within one polymeric architecture. Sulfonated poly(aryl ether ketone) nanomicelles were prepared by combining polymer sulfonation with solvent-induced self-assembly, and their structural features, dispersion stability, interfacial behavior, porous-media transport, and displacement performance were systematically evaluated. Spectroscopic characterization confirmed the successful introduction of sulfonic acid groups into the polymer backbone. The resulting nanomicelles exhibited an average hydrodynamic diameter of 117.8 nm, a polydispersity index of 0.186, and a zeta potential of −38.6 mV in deionized water, while a value of −27.4 mV was still maintained at a salinity of 150,000 mg/L, indicating good electrostatic stability under highly mineralized conditions. Further evaluation showed that the 0.30 wt% system retained a transmittance of 97.4% after 15 d of static standing, and its particle size remained at 151.7 nm even under 120 °C and 150,000 mg/L, demonstrating favorable thermal–salinity tolerance. At the same concentration, the oil–water interfacial tension decreased to 6.9 mN/m at 1800 s, while the contact angle of oil-aged quartz was reduced from 118.4° to 58.7°, indicating effective regulation of both the oil–water interface and the solid surface wettability. During microscopic displacement, the residual oil area fraction decreased from 32.8% after water flooding to 14.6%, and cluster-like oil, corner oil, and film-like oil were reduced from 14.6%, 9.8%, and 8.4% to 5.9%, 4.2%, and 4.5%, respectively. In core flooding, the incremental oil recovery reached 13.2%, the final water cut decreased to 81.2%, and the injection pressure increased only from 0.42 MPa to 0.68 MPa. These results indicate that sulfonated poly(aryl ether ketone) nanomicelles promote deep residual-oil mobilization through the combined effects of stable dispersion, interfacial regulation, and effective transport, with 0.30 wt% identified as the preferred concentration range. The main scientific contribution of this work is to establish a structure–dispersion–interface–transport–displacement relationship for SPAEK nanomicelles under deep-reservoir conditions, providing a polymeric nanomicelle-based strategy distinct from conventional surfactant, sulfonated polymer, and nanoparticle flooding systems. Full article

To improve the effectiveness of sulfonated polyacrylamide soft microgels (SMGs) in deep profile control, this study investigated a surfactant-assisted regulation strategy based on surfactant uptake and surfactant–microgel association. The uptake behavior of a hydroxysulfobetaine surfactant by SMGs was characterized, and the resulting changes in swelling, frequency-dependent elastic response, electrostatic stabilization, shear resistance, and long-distance transport were evaluated. The surfactant uptake process was well described by pseudo-second-order kinetics and a Langmuir-type saturation model, while FTIR and XPS analyses provided spectroscopic evidence for surfactant association with SMGs, especially at the particle surface. Compared with the SMG system, surfactant addition mildly reduced the swollen median size (D₅₀) at 15 d from 15.72 to 14.90 μm, and the corresponding swelling ratio decreased slightly but remained above 6.45. The S/SMG system also showed a larger magnitude of negative zeta potential, maintaining a value of −38.5 mV after 60 d compared with −32.1 mV for the SMG system, and generally better shear resistance, with particle size retention 0.8–3.8 percentage points higher over 0–7 d of swelling. Serial core-flooding experiments showed improved deep transport behavior. Although the SMG system produced slightly higher injection pressure below 2.4 m, the S/SMG system maintained a slightly higher pressure response beyond this distance. These results demonstrate that surfactant uptake and surface/network association regulate SMG physicochemical properties, thereby improving their transport and deep profile-control performance. Full article

Hydraulic fracturing in ultra-deep reservoirs faces significant challenges, including high wellbore friction and inadequate thermal stability of conventional fracturing fluids. To address these issues, we developed a potassium formate-weighted fracturing fluid with delayed crosslinking, excellent friction reduction, and superior temperature resistance, using a hydrophobic associating polymer thickener and a multi-ligand organic zirconium crosslinker. The weighted fracturing fluid has a density of 1.4 g/cm³ and completes crosslinking within 300 s at 90 °C. It achieves a maximum friction reduction rate of 63.2%. Below 60 °C, the system relies on a supramolecular thickener network for low viscosity and friction reduction; above 60 °C, chemical crosslinking between the thickener and zirconium ions creates a dual-network structure that significantly enhances temperature and shear resistance. After 120 min of shearing at 200 °C and 170 s⁻¹, the retained viscosity reaches 75.3 mPa·s. Complete gel breaking is achieved by sodium bromate via an oxidation reaction. This dual-network delayed crosslinking system successfully reconciles the conflict between low wellbore friction and high-temperature proppant-carrying capacity. This work presents a superior weighted fracturing fluid for ultra-deep reservoirs, as well as an innovative technique for their development. Full article

As oil and gas development increasingly targets low and ultra-low permeability reservoirs, conventional recovery techniques often prove insufficient for mobilizing residual oil. Surfactant flooding, a key chemical enhanced oil recovery (EOR) technology, thus requires careful system optimization and mechanistic investigation. This study focuses on low-permeability reservoirs in the Changqing Oilfield, evaluating three surfactant systems—YHS-Z1 (a 7:3 mass ratio blend of hydroxypropyl sulfobetaine and cocamide), YHS-Z2 (a polyether carboxylate, a nonionic-anionic composite) and a middle-phase microemulsion system (Heavy alkylbenzene sulfonate and hydroxysulfobetaine were combined with a mass ratio of 7:3)—through a series of experiments including interfacial tension measurement, contact angle analysis, static and dynamic oil displacement tests, as well as emulsion transport/retention index assessments, to comprehensively characterize their oil displacement properties. Based on the experimental data, this study constructed four classical regression models: Ridge Regression, Random Forest (RF), Gradient Boosting Regression (GBR), and Support Vector Regression (SVR), and conducted a comparative analysis of their predictive performance. The results demonstrate that the Random Forest (RF) model achieved the optimal prediction performance, with a Mean Absolute Error (MAE) of 1.8245, a Mean Absolute Percentage Error (MAPE) of 4.78%, and a coefficient of determination (R²) of 0.9428 on the training set. Further analysis using the SHapley Additive exPlanations (SHAP) algorithm revealed that the retention index is the primary global factor (accounting for 49.79% of the variance), while significant intergroup differences exist in the primary factors across different surfactant systems. Concurrently, single-factor and multi-factor sensitivity analyses were conducted to elucidate synergistic effects and threshold behaviors among parameters. The optimal parameter combination, identified via a random search method, achieved a predicted recovery factor of 45.61%, representing a 6.57% improvement over the highest experimental value. This study demonstrates that machine learning methods can effectively identify the dominant factors in oil displacement and enable synergistic parameter optimization, thereby providing a theoretical foundation for the efficient development of surfactant flooding in low-permeability reservoirs. Full article

In situ hydrogen generation can extend in situ combustion (ISC) by converting part of the heavy oil in place into H₂-containing gas while allowing part of the carbonaceous products to remain in the reservoir. To clarify how operating conditions affect hydrogen behavior, this study recalibrated key Arrhenius parameters in a pseudo-component kinetic network through least-squares-guided manual history matching against high-temperature/high-pressure (HTHP) reactor data obtained under three gas atmospheres (air, N₂, and CO₂). Model performance was evaluated through a direct comparison between raw simulator predictions and measured gas compositions using parity plots with a 1:1 reference line and residual-based statistics calculated from the simulated values rather than from regression-fitted values. The calibrated model was then used to compare hydrogen responses over 150–425 °C, 4–8 MPa, and 0.25–10 days. Within the tested range, three temperature regimes were identified: initiation (150–250 °C), pyrolysis-controlled (250–325 °C), and high-yield (325–425 °C). Oxygen and CO₂ generally reduced net hydrogen accumulation through competing pathways, whereas an inert N₂ background produced the highest H₂ fraction, reaching 28.6 vol% at 425 °C and 6 MPa after 10 days. These results provide a reactor-scale basis for selecting favorable operating windows and for subsequent reservoir-scale evaluation of in situ hydrogen generation under ISC conditions. Full article

The configurational stability and mobilizable oil release behavior of a multiscale gel–particle cooperative nested system within tight sandstone pore structures were systematically investigated. Scanning electron microscopy (SEM), atomic force microscopy (AFM), and μCT-based three-dimensional reconstruction were employed to characterize the multiscale structural features of the system. Interfacial regulation behavior was analyzed using contact angle measurements, oil–water interfacial tension (IFT), and zeta potential tests, while core flooding experiments were conducted to evaluate seepage response and oil displacement performance. The results indicate that particle reinforcement transforms the gel pore walls from a weakly rough interface into a strongly rough and mechanically interlocked structure, with the root-mean-square surface roughness increasing from 23.6 nm to 71.4 nm. μCT quantitative analysis shows that the pore volume fraction increases from 38.6% to 52.4%, and the connectivity ratio rises from 41.2% to 68.5, leading to the formation of a more continuous pore–throat network. Interfacial property measurements reveal that the rock surface contact angle decreases from 116.3° to 60.5°, and the oil–water interfacial tension is reduced from 27 mN·m⁻¹ to 3–5 mN·m⁻¹. Meanwhile, the system–rock interface exhibits a stronger overall negative surface charge. During displacement experiments, the pressure differential at 3.0 pore volumes (PV) is only 17.0 kPa, significantly lower than that of the control gel (26.2 kPa). The oil recovery is increased to 44.8%, while the residual oil saturation decreases from 0.46 to 0.32, and the displacement efficiency improves from 36.1% to 55.6%. These results demonstrate that the multiscale gel–particle cooperative nested system establishes a stable, regulated seepage configuration in tight sandstone and enables sustained mobilization of trapped oil under relatively low-pressure gradients through the coupled regulation of wettability, interfacial tension, and interfacial electrostatics. This study elucidates a coupled mechanism of configurational stability–flow channel redistribution–continuous oil mobilization and provides a new material design and regulation strategy for efficient recovery of residual oil in tight reservoirs. Full article

A Steam-and-Gas Push (SAGP) enhances energy efficiency in Steam-Assisted Gravity Drainage (SAGD) but induces gas fingering instabilities that limit the sweep efficiency. This study systematically investigates the impact of in situ-generated and externally injected Non-Condensable Gas (NCG) on fingering using fine-grid numerical simulations based on the Du-84 heavy oil reservoir. Two novel dimensionless indexes (heat–gas overlap index and Y-index) are introduced to quantitatively diagnose the fingering severity and heat transfer mechanisms. The results indicate that vertical chamber growth is convection-dominated by buoyant gas fingers, while lateral expansion remains conduction-dominated and stable. Reservoir heterogeneity significantly exacerbates fingering. An NCG concentration-dependent mechanism is established: low-dose co-injection (~0.5 mol%) suppresses minor fingering and increases oil production via a thin insulating gas cap. Conversely, excessive NCG (>5 mol%) thickens the gas cap, hindering heat transfer. Based on these mechanisms, a practical NCG operating window is proposed: a mid-stage, low-dose injection maximizes the production benefit (+4.4%), while a late-stage, moderate-dose injection (~5 mol%) enhances the oil–steam ratio (OSR) by 20.5% with minimal production loss (3.8%). This research offers critical guidance for optimizing NCG injections to mitigate fingering and improve recovery in heterogeneous reservoirs. Full article

Understanding how nanocomposite gels regulate pore–throat structures and flow behavior is essential for improving profile control and flow diversion in deep-water tight reservoirs. In this study, a dual-structure-regulated nanocomposite gel (DSRC-NCG) was designed, and its structure–flow coupling behavior during gel injection, curing, and degradation was systematically investigated using multiscale flow configurations, including microfluidic models, artificial cores, and sandpack systems. Microstructural evolution and pore–throat connectivity were characterized using μCT imaging, mercury intrusion porosimetry, nitrogen adsorption, and image-based flow simulations, while macroscopic flow responses were evaluated through permeability variation, dominant-channel evolution, injectivity behavior, and quantitative indices including the structure regulation index (SRI) and pore–flow matching index (HCI). The results show that increasing SiO₂ content induces a progressive optimization of pore–flow matching by refining critical throats and suppressing preferential flow channels, whereas excessive nanoparticle loading leads to aggregation and attenuation of these effects. This study proposes a multiscale structure–flow coupling framework that quantitatively connects pore–throat regulation with macroscopic flow responses during nanocomposite gel injection and degradation. These findings offer mechanistic insights and practical guidance for the design of nanocomposite gels with improved flow-regulation efficiency and reversibility in deep-water tight reservoir applications. Full article

To optimize enhanced oil recovery (EOR) techniques for pre-fractured heavy oil reservoirs, this research conducted long-core flooding experiments using three distinct injection media: CO₂, water, and CO₂/water alternate huff-n-puff. A 35 cm composite core was employed to simulate the reservoir conditions after pre-fracturing. Experimental results indicated that the CO₂ huff-n-puff process yielded the highest oil production, enhancing the overall recovery factor by 33.0% compared to depletion production, with a total recovery factor of 43.8% after four optimized cycles. The CO₂/water alternate huff-n-puff process increased the recovery factor by 28.3%, achieving a total of 41.9% after four cycles. In contrast, water injection improved the recovery factor by only 15.2%, reaching a total of 26.2% after three cycles. By evaluating both oil recovery efficiency and oil exchange ratio, the optimal cycle numbers were determined as four cycles for CO₂ huff-n-puff, four cycles for CO₂/water alternate huff-n-puff, and three cycles for water huff-n-puff. Based on these optimized parameters, the CO₂/water alternate huff-n-puff process was identified as the most effective EOR method for the target reservoir. Furthermore, this study assessed the potential for CO₂ storage in the reservoir post-production. Calculations of CO₂ storage ratios during the huff-n-puff process demonstrated the feasibility of integrating enhanced oil recovery with carbon sequestration. The findings provide a practical strategy for improving heavy oil recovery in low-permeability reservoirs while concurrently exploring the benefits of CO₂ storage. Full article

Low-salinity water flooding is a commonly used method to enhance oil recovery. At the microscopic scale, changes in pore structure and the distribution of remaining oil are critical to the effectiveness of water flooding. However, current research on the relationship between pore structure and remaining oil distribution is relatively limited. Therefore, this study employed micro-CT technology to analyze changes in pore structure and the distribution characteristics of remaining oil in sandstone cores during the water flooding process. Micron CT technology provides non-destructive, high-resolution three-dimensional imaging, clearly revealing the dynamic changes in the oil-water interface and remaining oil. The experiments included water saturation, oil saturation, and multi-stage water displacement processes in sandstone cores with different permeability values. The results show that the oil saturation in the rock core decreases during water flooding, and the morphology of remaining oil changes with increasing water flooding volume: cluster-like remaining oil decreases rapidly, while porous and membrane-like remaining oil gradually transforms, and columnar and droplet-like remaining oil increases under specific conditions. The study results indicate that at 1 PV flooding volume, the crude oil recovery rate reaches 57.56%; at 5 PV, the recovery rate increases to 64.00%; and at 100 PV, the recovery rate reaches 75.53%. This indicates that water flooding significantly improves recovery rates by enhancing wettability and capillary forces. Meanwhile, pore connectivity decreases, and particle migration becomes prominent, especially for particles smaller than 20 μm. These changes have significant impacts on remaining oil distribution and recovery rates. This study provides microscopic evidence for optimizing reservoir development strategies and holds important implications for enhancing recovery rates in mature oilfields. Full article

Data-driven modeling methods have been preliminarily applied in the development of tight-gas reservoirs, demonstrating unique advantages in post-fracturing productivity prediction. However, most of the established predictive models are “black-box” models, which provide productivity predictions based on a set of input parameters without revealing the internal prediction mechanisms. This lack of transparency reduces the credibility and practical utility of such models. To address the challenges of poor performance and low trustworthiness of “black-box” machine learning models, this study explores a data-driven approach to “black-box” predictive modeling by integrating ensemble learning with interpretability methods. The results indicate the following: The post-fracturing productivity prediction model for tight-gas reservoirs developed in this study, based on ensemble learning, achieves a goodness of fit of 0.923, representing a 26.09% improvement compared to the best-performing individual machine learning model. The stacking ensemble model predicts post-fracturing productivity for horizontal wells more accurately and effectively mitigates the prediction biases of individual machine learning models. An interpretability method for the “black-box” ensemble learning-based productivity prediction model was established, revealing the ranked importance of factors influencing post-fracturing productivity: reservoir properties, controllable operational parameters, and rock mechanics. This ranking aligns with the results of orthogonal experiments from mechanism-driven numerical models, providing mutual validation and enhancing the credibility of the ensemble learning-based productivity prediction model. In conclusion, this study integrates mechanistic numerical models and data-driven models to explore the influence of various factors on post-fracturing productivity. The cross-validation of results from both approaches underscores the reliability of the findings, offering theoretical and methodological support for the design of fracturing schemes and the iterative advancement of fracturing technologies in tight-gas reservoirs. Full article

Well-killing operations in water-sensitive hydrophilic formations are often complicated by extended well clean-up periods and, in some cases, failure to restore the well’s production potential post-kill. Typical development targets exhibiting these properties include the Neocomian and Jurassic deposits of fields in Western Siberia and Western Kazakhstan. This paper proposes a well-killing method incorporating simultaneous near-wellbore treatment. In cases where heavy oil components (asphaltenes, resins, or paraffins) are deposited in the near-wellbore zone, their removal with a solvent results in post-operation flow rates that exceed pre-restoration levels. For wells not affected by asphaltene, resin, and paraffin deposits, killing is performed using a blocking pill of invert emulsion stabilized with an emulsifier and hydrophobic nanosilica. During filtration into the formation, this emulsion does not break but rather reforms according to the pore throat sizes. Flow rates in such wells typically match pre-restoration levels. The described engineering solution proves less effective when the well fluid water cut exceeds 60%. For wells exhibiting premature water breakthrough that have not yet produced their estimated oil volume, the water source is identified, and water shutoff operations are conducted. This involves polymer-gel systems crosslinked with resorcinol and paraform, reinforced with inorganic components such as chrysotile microdispersions, micro- and nanodispersions of shungite mineral, and gas black. Oscillation testing identified the optimal additive concentration range of 0.6–0.7 wt%, resulting in a complex modulus increase of up to 25.7%. The most effective polymer-inorganic composite developed by us, incorporating gas black, demonstrates high water shutoff capability (residual resistance factor ranges from 12.5 to 65.0 units within the permeability interval of 151.7 to 10.5 mD). Furthermore, the developed composites exhibit the ability to selectively reduce water permeability disproportionately more than oil permeability. Filtration tests confirmed that the residual permeability to oil after placing the blocking composition with graphene is 6.75 times higher than that to water. Consequently, such treatments reduce the well water cut. Field trials confirmed the effectiveness of the developed polymer-inorganic composite systems. Full article

To improve fracturing support efficiency of terrestrial shale oil reservoirs with uneven proppant placement, this study used complex mesh flat-plate simulations and ANSYS FLUENT (2020) simulations to test four sand addition processes. Proppants were 70/140 mesh quartz sand with a density of 2650 kg/m³ and 40/70 mesh ceramic particles with a density of 2000 kg/m³, and the carrier was hydroxypropyl guar gum fracturing fluid with a viscosity of 4.46–13.4 mPa·s at 25 °C. Alternating sand addition performed best: sand-laying efficiency reached 52 percent, 10 percentage points higher than continuous sand addition and 12 percentage points higher than mixed sand addition; sand embankment void area was 1400 cm², 18.3 percent lower than continuous sand addition; proppant entry into secondary cracks increased 23.8 percent compared with reverse sand addition; at branch crack Position 2, 1.3 m from the inlet and at a 90-degree angle, its equilibrium height was 210 mm and paving rate 0.131. This study fills gaps of no systematic multi-process comparison and insufficient quantification of crack geometry–sand parameter coupling in existing research; its novelty lies in the unified visualization comparison of four processes, revealing geometry–parameter coupling and integrating experiment simulation; the optimal scheme also improves fracture support efficiency 21.5 percent compared with conventional continuous sand addition. Full article

In this study, a novel semi-liquid gel material based on bisphenol A-type epoxy resin (E51), methylhexahydrophthalic anhydride (MHHPA), and epoxidized soybean oil (ESO) was developed for high-performance wellbore sealing. The gel system exhibits tunable gelation times ranging from 1 to 10 h (±0.5 h) and maintains a low viscosity of <100 ± 2 mPa·s at 25 °C, enabling efficient injection into the wellbore. The optimized formulation achieved a compressive strength exceeding 112.5 ± 3.1 MPa and a breakthrough pressure gradient of over 50 ± 2.8 MPa/m with only 0.9 PV dosage. Fourier transform infrared spectroscopy (FTIR) confirmed the formation of a dense, crosslinked polyester network. Interfacial adhesion was significantly enhanced by the incorporation of 0.25 wt% octadecyltrichlorosilane (OTS), yielding an adhesion layer thickness of 391.6 ± 12.7 nm—approximately 9.89 times higher than that of the unmodified system. Complete degradation was achieved within 48 ± 2 h at 120 °C using a γ-valerolactone and p-toluenesulfonic acid solution. These results demonstrate the material’s potential as a high-strength, injectable, and degradable sealing solution for complex subsurface environments. Full article